Chapter 3 General Principles in Simulation
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1 Chapter 3 General Principles in Simulation Banks, Carson, Nelson & Nicol Discrete-Event System Simulation Concepts In Discrete-Event Simulation System A collection of entities (people and machines..) that interact together over time for one or more goals Model An abstract representation of a system, usually containing structural, logical or mathematical relationship that describe a system in term of state, entities and their attributes, sets, processes, System state A collection of variables in any time that describe the system Entity Any object or component in system that require explicit representation (server, customer,...) Attributes The properties of a given customer List A collection of associated entities, ordered in some logical fashion (FIFO, priority,) ٢
2 Concepts In Discrete-Event Simulation (cont.) Event An instantaneous occurrence that changes the state of a system Event Notice A record of a event to occur at the current or future time (type and time) Event List FEL (future event list) Activity (unconditional wait) A duration time of specified length (service time or interarrival time, ) Deterministic, Statistical and functional Delay (conditional wait) A duration of time of unspecified indefinite length, which is not known until it ends (customer delay in waiting line) Clock A variable representing simulated time ٣ Able-Baker Call center System state LQ(t): the number of callers waiting to serve LA(t): or indicate Able is idle or busy LB(t): or indicate Baker is idle or busy Entities Caller Events Arrival event, service completion by Able or Baker Activities Service time by Able/Baker and Inter-arrival time Delay A caller wait in queue until Able or Baker becomes free ٤
3 Event scheduling How does each event affect system state, attributes? How activities are defined (deterministic, probabilistic,)? Which events trigger the beginning of each delay? What is system state at time? ٥ Event scheduling (cont.) Clock System state Attributes Future Event List (FEL) Cumulative statistics and counters t (x,y,z,) (3,t) (,t) (4,tn) T<t<T<n FEL is ordered by event time ٦
4 Event scheduling/time-advance algorithm Clock System state Future Event List (FEL) t (5,,6) (3,t) (,t) (5,t3) t<t*<t3 (4,tn) Clock System state Future Event List (FEL) Cloc k System state Future Event List (FEL) t (5,,5) (,t) (5,t3) t (5,,5) (,t) (4,t*) (5,t3) (4,tn) (4,tn) ٧ Generation Arrival Stream by Bootstrapping ٨
5 The stop time of simulation AT time the simulation stop time is specified,t E Run length TE is determined by the simulation itself. The time of occurrence of some specified events ٩ World views of Model for simulation (Three Types) Polling And Interrupt Event-scheduling world view We concentrate on events and their effects on system Process-interaction world view (like processes in OS) We define the model in terms of entities or objects and their life cycle of an entity It has intuitive appeal and allow to describe the process flow in terms of high level block or network constructs Event scheduling is hidden Both use a variable time advance (clock is advanced to next imminent event) Activity scanning world view Use fixed time increment and rule based approach to decide which activity can begin At each clock advance the conditions for each activity are checked and if they are true then corresponding activity begins It is suitable for small system It is very fast ١٠
6 Activity scanning example (Gate simulation) us 3us us us ١١ Two customer processes interaction in single server queue ١٢
7 Event Scheduling example (Grocery Center) System State LQ(t),LS(t) Entities The server and customer are not explicitly modeled Events Arrival (A), Departure (D), Stopping event (E=6) Event notices (A,t), (D,t), (E,6) Activities Inter-arrival time, service time Delay Customer time spent in waiting time ١٣ Execution of the arrival event ١٤
8 Execution of the departure event ١٥ Simulation Table clock System state LQ(t) LS(t) Future Event List Comment Cumulativ e Statistics B MQ (A,)(D,4)(E,6) First A occures (a*=) schedule next A (s*=4) schedule first D (A,)(D,4)(E,6) Second A occures:(a,) (a*=) schedule next A (Customer delayed) (D,4) (A,8)(E,6) Third A occures:(a,) (a*=6) schedule next A (Two customer delayed) 4 (D,6) (A,8)(E,6) First D occures:(d,4) (s*=) schedule next D (Customer delayed) ١٦
9 Computing Mean Response Time (cont.) Entities (Ci,t), representing customer Ci who arrive at time t Event notices (A,t,Ci), the arrival of customer Ci at future time t (D,t,Cj), the departure of customer Cj at future time t Set CHECKOUT LINE the set of all customers currently at the checkout counter, ordered by time of arrival Response time CLOCK TIME-attribute time of arrival S:sum of customer response time N D : all number of customers that currently are departure F:Total number of customers that spend more than 5 minutes in system ١٧ Simulation Table clock System state LQ(t) LS(t) CHECKOUT LINE Future Event List S Cumulative Statistics N D F (C,) (A,,C)(D,4,C)(E,6) (C,)(C,) (A,,C3)(D,4,C)(E,6) (C,)(C,) (C3,) (D,4,C) (A,8,C4)(E,6) 4 (C,) (C3,) (D,6,C) (A,8,C4)(E,6) ١٨
10 List Processing List processing is base of event management in event and process orientation systems. ١٩ Structure of a simulation system ٢٠
11 Event Scheduling Example ٢١
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